Probability of Ship on Collision Courses Based on the New PAW Using MMG Model and AIS Data

• Autorzy: Asmara I.P.S. , Kobayashi E. , Artana K.B.

Identyfikatory

DOI

10.12716/1001.09.01.05

• Języki publikacji: EN

Abstrakty

EN

This paper proposes an estimation method for ships on collision courses taking crash astern maneuvers based on a new potential area of water (PAW) for maneuvering. A crash astern maneuver is an emergency option a ship can take when exposed to the risk of a collision with other ships that have lost control. However, lateral forces and yaw moments exerted by the reversing propeller, as well as the uncertainty of the initial speed and initial yaw rate, will move the ship out of the intended stopping position landing it in a dangerous area. A new PAW for crash astern maneuvers is thus introduced. The PAW is developed based on a probability density function of the initial yaw rate. Distributions of the yaw rates and speeds are analyzed from automatic identification system (AIS) data in Madura Strait, and estimated paths of the maneuvers are simulated using a mathematical maneuvering group model.

Słowa kluczowe

EN

Modeling of Maneuvering of Ships; Crash Astern Maneuvers; anticollision; mathematical model; Maneuvering; Potential Area of Water (PAW); Automatic Identification System (AIS); AIS Data

• Wydawca: Faculty of Navigation, Gdynia Maritime University
• Czasopismo: TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
• Rocznik: 2015
• Tom: Vol. 9, no. 1
• Strony: 43--50
• Opis fizyczny: Bibliogr. 10 poz., rys., tab.

Twórcy

autor

Asmara I.P.S.

• Graduate School of Maritime Sciences, Kobe University, Japan Politeknik Perkapalan Negeri Surabaya, Indonesia

autor

Kobayashi E.

• Graduate School of Maritime Sciences, Kobe University, Japan

autor

Artana K.B.

• Institut Teknologi Sepuluh Nopember Surabaya, Indonesia

Bibliografia

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• 3 Goerlandt, F. & Kujala, P. 2011. Traffic Simulation Based Ship Collision Probability Modeling. Reliability Engineering and System Safety 96: 91‐107.
• 4 Inoue, K. 1990. Concept of Potential Area of Water as an Index for Risk Assessment in Ship Handling. The Journal of Navigation 43(1):1‐7.
• 5 Kobayashi, E. 1995. The Development of Practical Simulation System to Evaluate Ship Maneuverability in Shallow Water; Proceedings of the Sixth International Symposium on Practical Design of Ships and Mobile Unites (PRADS ’95), Seoul,17‐22 September 1995.
• 6 Kristiansen, S. 2005. Maritime Transportation: Safety Management and Risk Analysis. Oxford: Butterworth‐ Heinemann, Traffic‐Based Model: 133‐171.
• 7 Mulyadi, Y. Kobayashi, E. Wakabayashi, N. Pitana, T. & Wahyudi 2014. Development of Ship Sinking Frequency Model Over Subsea Pipeline for Madura Strait Using AIS Data. WMU Journal of Maritime Affairs 13(1): 53‐59.
• 8 Yoshimura, Y. & Masumoto, Y. 2012. Hydrodynamic Database and Maneuvering Prediction Method with Medium High‐Speed Merchant Ships and Fishing Vessels; Proceedings of International MARSIM Conference, Singapore, 23‐27 April 2012.
• 9 Yoshimura, Y. & Nomoto, K. 1978. Modeling of Maneuvering of Ships with a Propeller Idling, Boosting and Reversing. The Society of Naval Architects of Japan 144, 57‐69 (in Japanese).
• 10 Yoshimura, Y. 1980. Mathematical model and Application of Maneuvering Behavior with a Propeller Idling, Boosting and Reversing. Doctoral Dissertation of Hokkaido University, Japan (in Japanese)